Abstract:

NC-AFM is an experimental technique that is capable of imaging, in principle, any surface at atomic resolution in any environment. Despite the clear advantages of NC-AFM, the biggest drawback is with regards to the interpretation of the results. Typically theoretical simulations are conducted to assist with this. A key component in linking theoretical simulations and the experimental results is the use of virtual machines. These aim to reproduce the experiment, allowing for a more complete simulation. The PyVAFM presented within, is such a virtual machine allowing users to reproduce any experimental setup or operational mode. It is fully open source, allowing future users to update the software with new cutting edge experimental components.

Solid-liquid interfaces play a key role in many natural processes such as weathering or biomineralisation. In order to understand these processes, it is important to gain insight into the atomic structure behind them. Exploration of solid-liquid interfaces by NC-AFM is common, although due to the additional complexity of the environment as well as the experiment, the measured signal is difficult to relate to physical processes. As part of this work, we examine experimental results of Frequency Modulated-Atomic Force Microscopy (FM-AFM) on calcite in water and reproduce them using the PyVAFM, in an attempt to understand them in terms of average tip-sample distance. Building upon this we also considered steps on a calcite surface, studied using a new high speed AFM set-up. It was found that a shadow appeared at the step edge that was previously unseen. Using a combination of molecular dynamics and simulated AFM images we developed a model of the shadow region giving insight into the dissolution process.

A chemically similar material to calcite, dolomite contains a similar crystal structure, but every second Ca is replaced with a Mg. Up until now identification of chemically alike species with the same surface charge has not been demonstrated in liquids and represents a new benchmark in sensitivity. By comparing the subtle differences in FM-AFM frequency shift curves as well as the simulated water densities above the various cations, it was possible for us to identify the Mg and Ca sites on dolomite.

The main theme linking all these topics is in the analysis of NC-AFM images. From this it is clear that it still remains challenging and is typically done by eye. This is a very subjective approach and unscientific. In this final section we endeavour to produce an algorithm that uses Fourier analysis of images to produce a score of how similar the two images are. We produced an algorithm that is insensitive to phase, rotation, scale and resolution and designed specifically for comparison of NC-AFM images, allowing increased objectivity when making such comparisons.